MétaCan
Menu
Back to cohort
Record W4393243007 · doi:10.31186/naturalis.12.1.26715

Evaluasi Kesesuaian Lahan Sawah Berdasarkan Status Hara di Kecamatan Seluma Selatan Kabupaten Seluma

2023· article· en· W4393243007 on OpenAlex
Hendrio Afrisa

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNaturalis Jurnal Penelitian Pengelolaan Sumber Daya Alam dan Lingkungan · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Agroindustry Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsForestryGeography

Abstract

fetched live from OpenAlex

The low productivity of rice in Seluma Selatan District is caused by fertilization actions based on general recommendations and not based on site-specific recommendations. In fact, fertilization should be based on soil nutrient status, especially N, P and K. This study aims to determine the nutrient status and evaluate the suitability class of lowland rice in Seluma Selatan District, Seluma Regency. This study used survey methods, soil sampling, and laboratory analysis, then matched it with the soil fertility level classification system and land suitability classification. The results showed that the nutrient status of paddy fields in Seluma Selatan sub-district in low-medium rice fields was categorized. It is characterized by an acidic pH value and low P2O5 in providing nutrients for lowland rice plants. Evaluation of land suitability in Seluma Selatan sub-district shows that the land suitability classes are S2 and S3. The results of the evaluation of the most suitable land suitability for land unit 2 (Au.1.1.1) were quite suitable for S2n with available nutrient limiting factors at the P2O5 level and marginally suitable for S3n on land unit 4 (Hab.1.1.1) with available nutrient limiting factors at P2O5 and K2O levels. Efforts to improve the suitability class S2 (fairly suitable) can be increased to S1 class (very suitable) and the S3 land suitability class (marginally appropriate) can be increased to S2 (quite suitable) . Keywords: Land suitability, lowland rice, nutrient status

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.256
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it